Hascontributedto an open-source AIprojectIs excitedabout thepotential ofLLMs ineducationHas traveledinternationallyto attend thisconferenceHas used anLLM tosummarizeresearchpapersCan namethreedifferent LLMarchitecturesHas apreferred AIresearch toolthey canrecommendHas used agenerative AImodel tocreate art ormusicCanrecommenda good AI ortech relatedpodcastIs interestedin the ethicalimplicationsof generativeAIHaspublishedresearch onmultilingualLLMsHasparticipated ina hackathonfocused on AIor LLMsHas collaboratedon a researchpaper withsomeone from adifferent continentIs familiarwith theconcept ofpromptengineeringCan explain thedifferencebetween causaland maskedlanguagemodelsHas presenteda paper onnaturallanguagegenerationHasattended anICMLconferencebeforeKnows atleast threeprogramminglanguagesHasexperiencewith fine-tuning a pre-trained LLMHas learneda newlanguage inthe last yearIs currentlyworking on aprojectinvolving cross-lingual transferlearningIs optimisticabout thefuture ofhuman-AIcollaborationHas used agenerative AImodel for anon-academicpurposeHassuccessfullydebugged acomplexLLMHas experiencewith low-resourcelanguages inNLPHascontributedto an open-source AIprojectIs excitedabout thepotential ofLLMs ineducationHas traveledinternationallyto attend thisconferenceHas used anLLM tosummarizeresearchpapersCan namethreedifferent LLMarchitecturesHas apreferred AIresearch toolthey canrecommendHas used agenerative AImodel tocreate art ormusicCanrecommenda good AI ortech relatedpodcastIs interestedin the ethicalimplicationsof generativeAIHaspublishedresearch onmultilingualLLMsHasparticipated ina hackathonfocused on AIor LLMsHas collaboratedon a researchpaper withsomeone from adifferent continentIs familiarwith theconcept ofpromptengineeringCan explain thedifferencebetween causaland maskedlanguagemodelsHas presenteda paper onnaturallanguagegenerationHasattended anICMLconferencebeforeKnows atleast threeprogramminglanguagesHasexperiencewith fine-tuning a pre-trained LLMHas learneda newlanguage inthe last yearIs currentlyworking on aprojectinvolving cross-lingual transferlearningIs optimisticabout thefuture ofhuman-AIcollaborationHas used agenerative AImodel for anon-academicpurposeHassuccessfullydebugged acomplexLLMHas experiencewith low-resourcelanguages inNLP

Human BINGO: Navigating Generative AI and LLMs Across Languages - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Has contributed to an open-source AI project
  2. Is excited about the potential of LLMs in education
  3. Has traveled internationally to attend this conference
  4. Has used an LLM to summarize research papers
  5. Can name three different LLM architectures
  6. Has a preferred AI research tool they can recommend
  7. Has used a generative AI model to create art or music
  8. Can recommend a good AI or tech related podcast
  9. Is interested in the ethical implications of generative AI
  10. Has published research on multilingual LLMs
  11. Has participated in a hackathon focused on AI or LLMs
  12. Has collaborated on a research paper with someone from a different continent
  13. Is familiar with the concept of prompt engineering
  14. Can explain the difference between causal and masked language models
  15. Has presented a paper on natural language generation
  16. Has attended an ICML conference before
  17. Knows at least three programming languages
  18. Has experience with fine-tuning a pre-trained LLM
  19. Has learned a new language in the last year
  20. Is currently working on a project involving cross-lingual transfer learning
  21. Is optimistic about the future of human-AI collaboration
  22. Has used a generative AI model for a non-academic purpose
  23. Has successfully debugged a complex LLM
  24. Has experience with low-resource languages in NLP